• Announcement
• New and improved
• Fixes

Release Information

• Release date of Data Quality & Observability Classic 2025.09: September 29, 2025
• Release notes publication date: September 2, 2025

New and improved

Platform

Warning To continue using SQL Assistant for Data Quality, you must upgrade to Data Quality & Observability Classic version 2025.09. This version utilizes the gemini-2.5-pro AI model. After this date, SQL Assistant for Data Quality will stop working unless you upgrade, as Google will retire the gemini-1.5-pro-002 model used in earlier versions of Data Quality & Observability Classic.

Note We updated Tomcat to address several security vulnerabilities (CVEs). The maximum part size for multipart requests is now set to 80 by default. This default limit might affect APIs that process datasets with an large number of columns. If necessary, you can change this limit using the property "DQ_SERVLET_MULTIPART_MAXPARTCOUNT" in the owl-env.sh file for Spark Standalone installations or the owl-web-configmap for Kubernetes environments.

• You can now configure Secret Key-based encryption in Data Quality & Observability Classic environments. This allows you to use an existing JKS file or override it with your own file for greater control over key size, algorithms, and encryption methods.
• When you delete a tenant from the metastore, the schema and all its tables are also deleted.

Jobs

• BigQuery Pushdown jobs now support column names with spaces.

Findings

• We removed the "State" column from the Rules tab on the Findings page to improve readability and streamline the layout.
• The Lower Bound and Upper Bound input fields for adaptive rules on the Change Detection modal now replace commas with periods, ensuring that values such as 10,23 are interpreted and displayed as 10.23. This prevents locale-specific misinterpretations.

Rules

• The column order in the Preview Breaks dialog box now matches the column order on the Rule Query page.
• The values for rules, data preview, and rule preview now show full numeric values instead of exponential values.

Dataset Overview

• You can now analyze tables in schemas with mixed or lowercase Snowflake schema names without editing the dataset query. This applies to both Pushdown and Pullup, making the analysis process more seamless.

Dataset Manager

• You can now use the updated APIs to manage the new "Schema Table Mapping" field available in the Dataset Edit dialog box in the Dataset Manager. Use the "/v2/updatecatalogobj" API to update this field and the "/v2/getdatasetschematablemapping" API to retrieve the Schema Table Mapping JSON string. Existing authorization rules now apply to schema mapping API updates, ensuring consistent security. Additionally, the scope query parser now supports multiple schemas and tables, and cardinality has been enhanced to allow multiple tables in a single job. This advanced SQL parsing is executed for each Data Quality & Observability Classic job when the new field, schemaTableNames, is empty or Null.
• When you edit a dataset in Dataset Manager, the "Schema Table Mapping" field is now automatically updated during the next job execution if it is empty or blank. The new parsing algorithm uses the scope query schema and table discovery to populate this field, ensuring more accurate and complete dataset information.
• You can now see a new read-only "Dataset Query" field in the Dataset Edit dialog box. This field shows the variables used in the query, making it easier to review the dataset's configuration.

Collibra Platform integration

• You can now associate a single data asset with multiple tables. The cardinality of the "Data Asset Represent Table" relation type has been updated from one-to-one to one-to-many, allowing for greater flexibility in managing data asset relationships.

Fixes

Platform

• On the Quality tab of Collibra Platform, the ring chart color now matches the corresponding ring chart in the At a Glance sidebar.

Jobs

• Pushdown jobs no longer fail with a "ConcurrentDeleteReadException" message caused by concurrent delete and read operations in a Delta Lake environment.
• Potential errors in the estimation step caused by complex source queries are now resolved.

Rules

• You can now preview the results of your rule on jobs from SQL Server connections using Livy without the application becoming unresponsive.
• When a SQL rule contains multiple column names and the MAP_TO_PRIMARY_COLUMN option is enabled during integration setup, only the primary column name is now assigned to the data quality rule asset.
• The "Actions" drop-down list on the Templates page no longer forces a selection.
• En dash (–) comments in the SQL source query no longer cause the rule to throw an exception.

Dataset Manager

• You can now find renamed datasets in the Dataset Manager.

Collibra Platform integration

• The lowest possible passing fraction is now 0 when a dataset from Data Quality & Observability Classic is integrated with Collibra Platform, even if the total number of outlier findings would otherwise result in a negative passing fraction value.
• You no longer receive an unexpected error stating “unable to fetch DGC schemas” when mapping connections from Data Quality & Observability Classic to databases in Collibra Platform.
• The dgc_dq_mapping table now includes an alias for column names, ensuring the correct column relation is reflected in the data quality rule.